RaBitQ is an open-source library implementing the "Quantizing High-Dimensional Vectors with a Theoretical Error Bound for Approximate Nearest Neighbor Search" method, providing vector quantization and compression techniques designed to improve efficiency and accuracy of ANN search engines and vector databases operating in high-dimensional spaces.
Category: SDKs & Libraries
Slug: rabitq
Source: https://github.com/gaoj0017/RaBitQ
RaBitQ is an open-source implementation of the SIGMOD 2024 method "Quantizing High-Dimensional Vectors with a Theoretical Error Bound for Approximate Nearest Neighbor Search." It provides vector quantization and compression techniques aimed at improving the efficiency and accuracy of approximate nearest neighbor (ANN) search engines and vector databases operating in high-dimensional spaces.
./data/ with detailed instructions in ./data/README.md../src/ivf_rabitq.h.space.h, fast_scan.h)../results/.technical_report.pdf) and published paper citation information for research use../src/../data/README.md.src directory../results/ directory.LICENSE file (see GitHub project for exact terms).Loading more......